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Grey Scale Skeletonisation with Curvature Sensitive Noise Damping

  • Huaijun Qiu
  • Edwin R. Hancock
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3138)

Abstract

This paper describes a method for curvature dependent skeletonisation in grey-scale images. We commence from a magnetostatic analogy, where the tangential edge flow is intepretted as a current. A vector potential is constructed by integrating the current weighted by inverse distance over the image plane. The skeleton corresponds to the location of valley lines in the vector potential. To damp noise effects we damp the current with an exponential function of the local curvature. In addition, we describe a number of postprocessing steps that can be used to improve the quality of the detected skeletons. In the end, we compare the effects of two alternative ways for noise damping.

Keywords

Image Plane Vector Potential Synthetic Image Eikonal Equation Symmetry Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Huaijun Qiu
    • 1
  • Edwin R. Hancock
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK

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